Python 将numpy数组或列表附加到数据帧

大家好，我的问题与上述类似，但需要跨1k cols执行。 在解决上述链接的过程中，我遇到了一个意想不到的问题

假设我有一个数据帧df，如下所示：

col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5

col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5
new extension of rows when appending
1    1   .
1    23  .
1    43  .
Nan  .   Nan
Nan  .   Nan
Nan  .   Nan

columns = [list_of_columns_from_dataframe_]
        for i in columns:
        mean = df[i].mean()
        dev  = df[i].std()
        xx   = np.random.normal(mu, sigma, 20)
        xtra = {i: xx.tolist()}
        df   = df.append(pd.DataFrame(xtra))

在上面的几列中，我想用这个numpy数组扩展所有的列

xx = np.random.normal(mu, sigma, 413)

如何将其附加到输出如下的循环中：

col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5
new extension of rows when appending
1    1   .
1    23  .
1    43  .
.    .   .
.    .   .
.    .   .

当在for循环中使用时，来自链接的解决方案为我提供了一个我不期望的数据帧：

first iteration
col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5
new extension of rows when appending
1    Nan  .
1    Nan  .
1    Nan  .
    
@ second Iteration for the second column I get this 
col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5
new extension of rows when appending
1    Nan  .
1    Nan  .
1    Nan  .
Nan  1
Nan  23
Nan  43

但我所寻找的是这样的输出：

col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5

col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5
new extension of rows when appending
1    1   .
1    23  .
1    43  .
Nan  .   Nan
Nan  .   Nan
Nan  .   Nan

columns = [list_of_columns_from_dataframe_]
        for i in columns:
        mean = df[i].mean()
        dev  = df[i].std()
        xx   = np.random.normal(mu, sigma, 20)
        xtra = {i: xx.tolist()}
        df   = df.append(pd.DataFrame(xtra))

我的代码如下所示：

col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5

col1 col2 Col2 - col1000
0     1     3
1     2     4
2     3     7
3     4     5
new extension of rows when appending
1    1   .
1    23  .
1    43  .
Nan  .   Nan
Nan  .   Nan
Nan  .   Nan

columns = [list_of_columns_from_dataframe_]
        for i in columns:
        mean = df[i].mean()
        dev  = df[i].std()
        xx   = np.random.normal(mu, sigma, 20)
        xtra = {i: xx.tolist()}
        df   = df.append(pd.DataFrame(xtra))